BACKGROUND/OBJECTIVES: Dietary factors act on lower urinary tract symptoms (LUTS).This study examined the relationship between the overall diet quality and LUTS. SUBJECTS/METHODS: This study analyzed the data from examinees who visited a general hospital in Korea (October 13, 2014−March 12, 2020). The number of subjects in the study was 6,506 adult men. The recommended food score was used to evaluate the overall quality of the diet, and the International Prostate Symptom Score was used to quantify LUTS. Logistic regression analysis was used to derive the odds ratio (OR) and 95% confidence interval (CI) to evaluate the relationship between the dietary quality and LUTS. The influence of age, education, marital history, income, occupation, smoking, drinking, exercise, metabolic syndrome, body mass index (BMI), and prostate-specific antigen (PSA) level was analyzed to determine the net influence of the overall diet quality on LUTS. RESULTS: The group with high overall dietary quality showed a lower incidence of LUTS than the group with relatively lower dietary quality (OR, 0.88; 95% CI, 0.79–0.99). These results were also observed after correcting for other risk factors and associated variables: age, education, smoking, metabolic syndrome, BMI, and PSA level. CONCLUSION The overall diet quality and LUTS were correlated. Nevertheless, further research will be needed to find the relationship between diet quality and LUTS.

BACKGROUND/OBJECTIVES: Dietary factors act on lower urinary tract symptoms (LUTS).This study examined the relationship between the overall diet quality and LUTS. SUBJECTS/METHODS: This study analyzed the data from examinees who visited a general hospital in Korea (October 13, 2014−March 12, 2020). The number of subjects in the study was 6,506 adult men. The recommended food score was used to evaluate the overall quality of the diet, and the International Prostate Symptom Score was used to quantify LUTS. Logistic regression analysis was used to derive the odds ratio (OR) and 95% confidence interval (CI) to evaluate the relationship between the dietary quality and LUTS. The influence of age, education, marital history, income, occupation, smoking, drinking, exercise, metabolic syndrome, body mass index (BMI), and prostate-specific antigen (PSA) level was analyzed to determine the net influence of the overall diet quality on LUTS. RESULTS: The group with high overall dietary quality showed a lower incidence of LUTS than the group with relatively lower dietary quality (OR, 0.88; 95% CI, 0.79–0.99). These results were also observed after correcting for other risk factors and associated variables: age, education, smoking, metabolic syndrome, BMI, and PSA level. CONCLUSION The overall diet quality and LUTS were correlated. Nevertheless, further research will be needed to find the relationship between diet quality and LUTS.

BACKGROUND/OBJECTIVES: Dietary factors act on lower urinary tract symptoms (LUTS).This study examined the relationship between the overall diet quality and LUTS. SUBJECTS/METHODS: This study analyzed the data from examinees who visited a general hospital in Korea (October 13, 2014−March 12, 2020). The number of subjects in the study was 6,506 adult men. The recommended food score was used to evaluate the overall quality of the diet, and the International Prostate Symptom Score was used to quantify LUTS. Logistic regression analysis was used to derive the odds ratio (OR) and 95% confidence interval (CI) to evaluate the relationship between the dietary quality and LUTS. The influence of age, education, marital history, income, occupation, smoking, drinking, exercise, metabolic syndrome, body mass index (BMI), and prostate-specific antigen (PSA) level was analyzed to determine the net influence of the overall diet quality on LUTS. RESULTS: The group with high overall dietary quality showed a lower incidence of LUTS than the group with relatively lower dietary quality (OR, 0.88; 95% CI, 0.79–0.99). These results were also observed after correcting for other risk factors and associated variables: age, education, smoking, metabolic syndrome, BMI, and PSA level. CONCLUSION The overall diet quality and LUTS were correlated. Nevertheless, further research will be needed to find the relationship between diet quality and LUTS.

BACKGROUND/OBJECTIVES: Dietary factors act on lower urinary tract symptoms (LUTS).This study examined the relationship between the overall diet quality and LUTS. SUBJECTS/METHODS: This study analyzed the data from examinees who visited a general hospital in Korea (October 13, 2014−March 12, 2020). The number of subjects in the study was 6,506 adult men. The recommended food score was used to evaluate the overall quality of the diet, and the International Prostate Symptom Score was used to quantify LUTS. Logistic regression analysis was used to derive the odds ratio (OR) and 95% confidence interval (CI) to evaluate the relationship between the dietary quality and LUTS. The influence of age, education, marital history, income, occupation, smoking, drinking, exercise, metabolic syndrome, body mass index (BMI), and prostate-specific antigen (PSA) level was analyzed to determine the net influence of the overall diet quality on LUTS. RESULTS: The group with high overall dietary quality showed a lower incidence of LUTS than the group with relatively lower dietary quality (OR, 0.88; 95% CI, 0.79–0.99). These results were also observed after correcting for other risk factors and associated variables: age, education, smoking, metabolic syndrome, BMI, and PSA level. CONCLUSION The overall diet quality and LUTS were correlated. Nevertheless, further research will be needed to find the relationship between diet quality and LUTS.

BACKGROUND/OBJECTIVES: Dietary factors act on lower urinary tract symptoms (LUTS).This study examined the relationship between the overall diet quality and LUTS. SUBJECTS/METHODS: This study analyzed the data from examinees who visited a general hospital in Korea (October 13, 2014−March 12, 2020). The number of subjects in the study was 6,506 adult men. The recommended food score was used to evaluate the overall quality of the diet, and the International Prostate Symptom Score was used to quantify LUTS. Logistic regression analysis was used to derive the odds ratio (OR) and 95% confidence interval (CI) to evaluate the relationship between the dietary quality and LUTS. The influence of age, education, marital history, income, occupation, smoking, drinking, exercise, metabolic syndrome, body mass index (BMI), and prostate-specific antigen (PSA) level was analyzed to determine the net influence of the overall diet quality on LUTS. RESULTS: The group with high overall dietary quality showed a lower incidence of LUTS than the group with relatively lower dietary quality (OR, 0.88; 95% CI, 0.79–0.99). These results were also observed after correcting for other risk factors and associated variables: age, education, smoking, metabolic syndrome, BMI, and PSA level. CONCLUSION The overall diet quality and LUTS were correlated. Nevertheless, further research will be needed to find the relationship between diet quality and LUTS.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Background: Sleep apnea, characterized by interruptions in breathing during sleep, presents health risks and has been associated with various dietary patterns. This study aimed to investigate the relationship between dietary patterns, as measured by the Recommended Food Score (RFS), and the risk of sleep apnea, as assessed using the Berlin Questionnaire. Methods: A total of 11,586 adults from a general hospital in Korea were included in the analysis. Participants completed a questionnaire covering demographic factors, lifestyle behaviors, and dietary habits. Dietary quality was assessed using the RFS, while sleep apnea risk was evaluated using the Berlin Questionnaire. Logistic regression analysis was conducted to assess the impact of RFS on sleep quality, adjusting for potential confounding factors. Results: Higher RFS was negatively correlated with sleep apnea risk (odds ratio=0.91 [95% confidence interval, 0.82–1.00, P=0.048)]. Significant positive associations were observed between male sex, low education level, marital status, smoking, drinking, inactivity, high blood pressure, high waist circumference, high levels of triglycerides, and poor sleep quality. Hematologic markers such as C-reactive protein levels and glutamic pyruvic transaminase also displayed significant associations with sleep quality. Conclusions This study contributes to our understanding of the complex interplay between diet, lifestyle, metabolic health, and sleep quality. These findings underscore the importance of dietary interventions in managing sleep apnea and highlight avenues for further research.

Purpose: Wrestlers have a lot of direct skin-to-skin contact between wrestlers during matches, and many studies show that wrestlers are vulnerable to the spread of skin infections. However, there have been few studies on skin infections in Korean wrestlers. The purpose of this study was to compare the characteristics of skin diseases in wrestlers and other athletes. Methods: Athletes who visited for skin diseases in the Department of Family Medicine in the Jincheon National Training Center in 2018 were investigated. We calculated the duration of skin disease per training period (DSD/TP) as the number of visits×7 days×1,000/official training days. Athletes with a DSD/TP above the median value or equal to were defined as the high DSD/TP group, and the others were defined as the low DSD/TP group. A chi-square test was used to compare the odds ratio [OR] for these groups about infectious and noninfectious skin diseases. Results: Thirty wrestlers and 89 other sports players visited the infirmary with skin diseases. The probability of belonging to the high DSD/TP group was significantly higher when the wrestlers visited for skin infections than the other athletes (OR, 7.714; 95% confidence interval [CI], 2.699–22.048). However, there was no significant difference in noninfectious skin diseases between wrestling and other sports (OR, 0.569; 95% CI, 0.246–1.320). Conclusion This is the first study that shows Korean national wrestlers with skin diseases receive more treatment for infectious skin diseases than other sports. This study can provide important information on the prevention of wrestlers for skin infections.

Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data.The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4 + and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.